Providing intelligent file name suggestions

1. A method comprising:

training, based on characteristics of a plurality of previously named content items corresponding to a user account, a machine-learning model to identify a naming pattern associated with filenames of the plurality of previously named content items;

determining, by at least one processor and using the machine-learning model, a plurality of name segment suggestions comprising name segments for setting a filename of a content item associated with the user account;

providing, for display in a first portion of a graphical user interface, a plurality of graphical elements corresponding to the plurality of name segment suggestions for combining into the filename of the content item;

receiving a selection of two or more graphical elements from the plurality of graphical elements to insert into a filename portion in a second portion of the graphical user interface, the filename portion comprising the two or more graphical elements in a first order of graphical elements based on positions of the two or more graphical elements;

detecting, within the filename portion in the second portion of the graphical user interface, one or more inputs to select one or more graphical elements of the two or more graphical elements and modify a position of the one or more selected graphical elements within the filename portion to change the first order of graphical elements to a second order of graphical elements different than the first order of graphical elements; and

combining two or more name segment suggestions corresponding to the two or more graphical elements into the filename of the content item according to the second order in which the two or more graphical elements are positioned based on the modified position of the one or more selected graphical elements.

2. The method as recited in claim 1 , wherein determining the plurality of name segment suggestions for the content item comprises:

determining one or more characteristics of the content item; and

using the machine-learning model to determine the plurality of name segment suggestions based on the one or more characteristics of the content item.

3. The method as recited in claim 1 , further comprising:

preselecting one or more graphical elements from the plurality of graphical elements; and

auto-populating the filename of the content item with one or more corresponding name segment suggestions.

4. The method as recited in claim 1 , wherein detecting, within the filename portion in the second portion of the graphical user interface, the one or more inputs to select the one or more graphical elements of the two or more graphical elements and modify the position of the one or more selected graphical elements comprises detecting an input to drag a graphical element of the one or more selected graphical elements from a first position to a second position within the filename portion.

5. The method as recited in claim 4 , wherein modifying the position of the one or more selected graphical elements comprises changing the first order graphical elements to the second order of graphical elements within the filename portion in response to the input to drag the graphical element from the first position to the second position.

6. The method as recited in claim 1 , further comprising:

receiving a selection of an additional graphical element from the plurality of graphical elements; and

adding an additional name suggestion corresponding to the additional graphical element to the filename of the content item according to a position in which the additional graphical element is placed within the filename portion.

7. The method as recited in claim 1 , further comprising:

providing, for display in the first portion of the graphical user interface, a first set of graphical elements corresponding to a first category of name segments and a second set of graphical elements corresponding to a second category of name segments, the first set of graphical elements separate from the second set of graphical elements; and

receiving selections of a first selected graphical element added to the filename of the content item corresponds to a name segment suggestion from the first category of name segments and a second selected graphical element added to the filename of the content item corresponds to a name segment suggestion from the second category of name segments.

8. The method as recited in claim 1 , wherein:

determining the plurality of name segment suggestions for setting the filename of the content item associated with the user account comprises generating, using the machine-learning model, a plurality of scores for the plurality of name segment suggestions; and

providing the plurality of graphical elements corresponding to the plurality of name segment suggestions for setting the filename of the content item comprises selecting, for display in the graphical user interface and based on the plurality of scores for the plurality of name segment suggestions, the plurality of graphical elements.

9. The method as recited in claim 8 , wherein selecting the plurality of graphical elements comprises selecting a predetermined number of graphical elements.

10. The method as recited in claim 8 , wherein selecting the plurality of graphical elements comprises selecting graphical elements corresponding to name segment suggestions having scores that meet a predetermined threshold.

11. The method as recited in claim 1 , further comprising training the machine-learning model to identify a naming pattern based on weights according to a hierarchy of a plurality of user accounts associated with a related group of users.

12. The method as recited in claim 1 , further comprising:

detecting a text input comprising one or more manually entered characters within an input field associated with setting the filename of the content item; and

determining the plurality of name segment suggestions based on the text input and the naming pattern.

13. A system comprising:

at least one processor; and

a non-transitory computer readable storage medium comprising instructions that, when executed by the at least one processor, cause the system to:

identify characteristics of a plurality of previously named content items corresponding to a user account;

train, based on characteristics of the plurality of previously named content items corresponding to the user account, a machine-learning model to identify a naming pattern associated with filenames of the plurality of previously named content items;

determine, by the at least one processor and using the machine-learning model, a plurality of name segments for setting a filename of a new content item associated with the user account;

provide, for display in a first portion of a graphical user interface, a plurality of graphical elements corresponding to the plurality of name segments for combining into the filename of the new content item;

receive a selection of two or more graphical elements from the plurality of graphical elements to insert into a filename portion in a second portion of the graphical user interface, the filename portion comprising the two or more graphical elements in a first order of graphical elements based on positions of the two or more graphical elements;

detect, within the filename portion in the second portion of the graphical user interface, one or more inputs to select one or more graphical elements of the two or more graphical elements and modify a position of the one or more selected graphical elements within the filename portion to change the first order of graphical elements to a second order of graphical elements different than the first order of graphical elements; and

combine two or more name segments corresponding to the two or more graphical elements into the filename of the new content item according to the second order in which the two or more graphical elements are positioned based on the modified position of the one or more selected graphical elements.

14. The system as recited in claim 13 , further comprising instructions that, when executed by the at least one processor, cause the system to determine the plurality of name segments for setting the filename of the new content item by:

determining a characteristic of the new content item; and

determining, using the identified naming pattern, the plurality of name segments according to the determined characteristic of the new content item.

15. The system as recited in claim 14 , further comprising instructions that, when executed by the at least one processor, cause the system to determine the plurality of name segments according to the determined characteristic of the new content item by:

comparing the determined characteristic of the new content item to one or more characteristics of the plurality of previously named content items; and

selecting a name segment from a plurality of possible name segments based on a similarity of the characteristic of the new content item to the one or more characteristics of the plurality of previously named content items.

16. The system as recited in claim 13 , further comprising instructions that, when executed by the at least one processor, cause the system to auto-populate, using the machine-learning model, the filename of the new content item with one or more name segments based on one or more characteristics of the new content item.

17. The system as recited in claim 16 , further comprising instructions that, when executed by the at least one processor, cause the system to:

provide, for display in the graphical user interface, an option to remove the one or more name segments auto-populating the filename of the new content item; and

modify the filename of the new content item in response to a selection of the option to remove the one or more name segments from the filename of the new content item.

18. A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause a computer system to:

train, based on a plurality of content items previously stored in connection with a user account, a machine-learning model to identify a naming pattern associated with filenames of the plurality of content items;

determine, by the at least one processor and using the machine-learning model, a plurality of name segment suggestions comprising name segments for setting a filename of a content item associated with the user account;

provide, for display in a first portion of a graphical user interface, a plurality of graphical elements corresponding to the plurality of name segment suggestions for combining into the filename of the content item;

receive a selection of a two or more graphical elements from the plurality of graphical elements to insert into a filename portion in a second portion of the graphical user interface, the filename portion comprising the two or more graphical elements in a first order of graphical elements based on positions of the two or more graphical elements;

detect, within the filename portion in the second portion of the graphical user interface, one or more inputs to select one or more graphical elements of the two or more graphical elements and modify a position of the one or more selected graphical elements within the filename portion to change the first order of graphical elements to a second order of graphical elements different than the first order of graphical elements; and

combine two or more name segment suggestions corresponding to two or more graphical elements into the filename of the content item according to the order in which the two or more graphical elements are positioned based on the modified position of the one or more selected graphical elements.

19. The non-transitory computer readable storage medium of claim 18 , further comprising instructions that, when executed by the at least one processor, cause the computer system to:

determine the plurality of name segment suggestions for the content item by generating, using the machine-learning model, a plurality of scores for the plurality of name segment suggestions; and

provide the plurality of graphical elements corresponding to the plurality of name segment suggestions for setting the filename of the content item by selecting, for display in the graphical user interface and based on the plurality of scores for the plurality of name segment suggestions, a plurality of graphical elements.

20. The non-transitory computer readable storage medium of claim 18 , further comprising instructions that, when executed by the at least one processor, cause the computer system to train, based on a plurality of content items for a plurality of related user accounts, a machine-learning model to identify a naming pattern associated with the plurality of related user accounts.